Myocardial Involvement After Hospitalization for COVID-19 Complicated by Troponin Elevation: A Prospective, Multicenter, Observational Study

Background: Acute myocardial injury in hospitalized patients with coronavirus disease 2019 (COVID-19) has a poor prognosis. Its associations and pathogenesis are unclear. Our aim was to assess the presence, nature, and extent of myocardial damage in hospitalized patients with troponin elevation. Methods: Across 25 hospitals in the United Kingdom, 342 patients with COVID-19 and an elevated troponin level (COVID+/troponin+) were enrolled between June 2020 and March 2021 and had a magnetic resonance imaging scan within 28 days of discharge. Two prospective control groups were recruited, comprising 64 patients with COVID-19 and normal troponin levels (COVID+/troponin−) and 113 patients without COVID-19 or elevated troponin level matched by age and cardiovascular comorbidities (COVID−/comorbidity+). Regression modeling was performed to identify predictors of major adverse cardiovascular events at 12 months. Results: Of the 519 included patients, 356 (69%) were men, with a median (interquartile range) age of 61.0 years (53.8, 68.8). The frequency of any heart abnormality, defined as left or right ventricular impairment, scar, or pericardial disease, was 2-fold greater in cases (61% [207/342]) compared with controls (36% [COVID+/troponin−] versus 31% [COVID−/comorbidity+]; P<0.001 for both). More cases than controls had ventricular impairment (17.2% versus 3.1% and 7.1%) or scar (42% versus 7% and 23%; P<0.001 for both). The myocardial injury pattern was different, with cases more likely than controls to have infarction (13% versus 2% and 7%; P<0.01) or microinfarction (9% versus 0% and 1%; P<0.001), but there was no difference in nonischemic scar (13% versus 5% and 14%; P=0.10). Using the Lake Louise magnetic resonance imaging criteria, the prevalence of probable recent myocarditis was 6.7% (23/342) in cases compared with 1.7% (2/113) in controls without COVID-19 (P=0.045). During follow-up, 4 patients died and 34 experienced a subsequent major adverse cardiovascular event (10.2%), which was similar to controls (6.1%; P=0.70). Myocardial scar, but not previous COVID-19 infection or troponin, was an independent predictor of major adverse cardiovascular events (odds ratio, 2.25 [95% CI, 1.12–4.57]; P=0.02). Conclusions: Compared with contemporary controls, patients with COVID-19 and elevated cardiac troponin level have more ventricular impairment and myocardial scar in early convalescence. However, the proportion with myocarditis was low and scar pathogenesis was diverse, including a newly described pattern of microinfarction. Registration: URL: https://www.isrctn.com; Unique identifier: 58667920.


Inclusion and exclusion criteria
Inclusion criteria: hospitalised-recovering patient population (age ≥ 18 years), or those recently discharged from hospital, with a diagnosis of Covid-19 based upon either a pathology or radiology diagnosis, with cardiac biomarkers (troponin I or T) increased above the sex-specific upper reference limit of the local laboratory range. Exclusion criteria: being unable or unwilling to consent, contraindication to CMR, pregnancy or breast-feeding.

Recruitment and data collection of Covid-19 patients at acute phase
Screening was performed at an individual hospital level, with participating hospitals cross-referencing all admissions with a positive Covid-19 status (pathology/radiology diagnosis), with serum troponin results. The source data included hospital records, National Health Service (NHS) health and social care records, clinical and office charts, laboratory and pharmacy records as well as digital images from radiology (chest X-ray / computed tomography / CMR) and cardiology (echocardiography / angiography / CMR).
Clinical working diagnoses for raised troponin were extracted from the medical records by the research teams, during patient index admission, without knowledge of MRI results (which were performed prior to or shortly after hospital discharge). Teams were provided with a standard definition of Type 1 and Type 2 infarction1: a) Type 1 MI was defined as: the detection of a rise and/or fall of cTn with at least one value above the 99th percentile URL and with at least one of the following: -symptoms of acute myocardial injury -new ischemic electrocardiography changes -development of pathological Q waves -imaging evidence of new loss of viable myocardium or new regional wall motion abnormality in a pattern consistent with an ischemic aetiology -identification of a coronary thrombus by angiography including intracoronary imaging or by autopsy. b) Type 2 MI was defined as an MI occurring secondarily to myocardial ischaemia and an illness or process other than acute atherothrombosis. Possible mechanisms underlying this imbalance between myocardial oxygen demand and supply include coronary spasm, coronary embolism, coronary artery dissection, sustained tachyarrhythmia, severe bradyarrhythmia, severe hypertension, respiratory failure, shock, severe anaemia or hypotension.

Recruitment of controls
Contemporary patient cohorts acting as control data were acquired for comparative CMR analysis. These were derived from ethically approved local research studies from the recruiting centres for COVID HEART using the same CMR scanners (vendor and field strength). Control populations included: 1) A population matched for age and CVD risk factors, who have been hospitalised and are Covid ( +) and Troponin(−) [e.g. Capturing MultiORgan Effects of Covid-19 (C-MORE) cohort, Oxford, UK; NCT04510025].
2) A population matched for age and CVD risk factors, who have tested Covid(−) and Troponin(−). The control populations were recruited prospectively at five COVID HEART centres as part of on-going funded research (e.g. CISCO-19, PREDICT, C-MORE, OxAMI). As this is a longitudinal, observational study, co-enrolment with other UK Covid-19 studies/trials was permitted.

Consent procedures
All recruited patients gave written informed consent as per the international ethical and scientific quality standard of Good Clinical Practice (GCP). Patient information sheets for COVID-HEART were provided in English, and in up to 10 other languages commonly spoken in the UK (including: French, Portuguese, Polish, Urdu, Bengali, Punjabi, Gujarati, Hindi, Somali and Arabic), to facilitate engagement across a range of community groups. When eligibility criteria were confirmed, medical staff or appropriately trained support staff acquired consent from patients after allowing as much time as necessary to consider the study, or at least 24 h, whilst the patient was either an in-or out-patient. All participants had the right to withdraw from the study at any point. The reasons for withdrawals were recorded. If consent was withdrawn, or if the patient were to become incapacitated, any data collected up to that point remained on file and was included in the analysis.

ROLE OF THE FUNDING SOURCE
The funder had no involvement in: study design; collection, analysis, and interpretation of data; writing of the report; or the decision to submit for publication. A writing/analysis group (CB,MD,RD,VF,JG,AM,GM,JM,JA,HS,SP,GR,RY) oversaw image analysis at 3 corelabs (Oxford, Barts, Glasgow) and data transfer to the independent Glasgow Clinical Trials Unit. All authors have read and accepted the final version of the manuscript.

CMR PROTOCOL
The main CMR protocol was in keeping with Society for Cardiovascular Magnetic Resonance (SCMR) recommended CMR protocols for scanning patients with active or convalescent phase Covid-19 , and took approximately 50 min to acquire, with an optional shortened and extended protocol dependent of patient preference and ability. An estimated glomerular filtration rate (eGFR) and haematocrit were measured prior to each CMR scan. For patients with significant renal failure (eGFR < 30 ml/min/1.73 m2), late gadolinium enhancement (LGE) and post-contrast T1-mapping were omitted and a contrast-free CMR scan performed. The main CMR study protocol included the following components and typical parameters, which may vary by vendor and field strength, but remain comparable overall. A. Localiser sequences and breath-hold transverse Half-Fourier Acquisition Single-shot Turbo spin Echo (HASTE) imaging stacks covering lung and abdomen to 1-2 cm below the kidneys. Typical sequence parameters: TE 1.33ms, TR 700ms, slice thickness 8 mm, FOV = 400 mm, FOV phase 100%, flip angle 10°. B. Cine images acquired with breath-hold balanced steady-state free precession (bSSFP) sequence. Long axis views of the LV: 4-chamber, 2-chamber, and 3-chamber views. Ventricular short-axis stack. Sequence parameters matching the cine image acquisition in long-axis. Sequence parameters: TE 1.05ms, TR 40.29ms, slice thickness 8 mm, 25% distance factor, FOV = 500 mm, FOV phase 75%, flip angle 50°. C. Native (pre-contrast) Myocardial T1 and T2 mapping were acquired in 3 short-axis cuts of the LV (basal, midventricular, apical) using a single breath-hold shortened modified Look-Locker inversion (ShMOLLI) 5(1)1(1)1 technique, , where available. Shimming was performed to avoid artefacts. Native T1-mapping was acquired in 3 shortaxis cuts of the LV (basal, mid-ventricular, apical) to match the locations of segments 1-16 of the American Heart Association 17-segment model. he apical segment 17 was omitted. Typical pulse sequence parameters: TE 1.07ms, TR 379ms, slice thickness 8 mm, FOV = 360 mm FOV phase 75%, flip angle 35°, distance factor 25%, generalised autocalibrating partially parallel acquisition (GRAPPA) 2 with 24 reference lines. D. Native (pre-contrast) T2-mapping: matching in slice location to the T1 maps, was acquired using either a T2-prepped b-SSFP sequence with a minimum of 3 source images (e.g. MyoMaps T2-mapping for Siemens scanners), or a blackblood prepared, navigator-gated, free-breathing hybrid gradient (echo planar imaging, EPI) and spin-echo multi-echo sequence (GRASE). Typical sequence parameters: TE 1.3ms, TR 222.43ms, slice thickness 8 mm, FOV = 360 mm, FOV phase 80%, flip angle 20°. E.
LGE images were acquired ~ 5-15 min after intravenous injection of 0.1-0.15 mmol/kg of gadolinium-based contrast agent (GBCA, accepted GBCA agents include: gadobutrol and gadoteric acid.), with a free-breathing phase-sensitive motion correction bSSFP or breath-hold, segmented inversion-recovery sequence. Contiguous stack of LV short-axis images and single long-axis slices in 2-chamber, 4-chamber and 3-chamber at the same slice locations as obtained for cine imaging were acquired. A Look-Locker sequence was used to determine the appropriate inversion time (TI) . F. Post-contrast T1 measurements were acquired at the exact same locations as the native T1-maps and performed at least 10 min after injection of GBCA, using the same pulse sequence and parameters as the native T1-maps.

CMR ANALYSIS
CMR data sets were analysed within a disseminated core-lab (Barts structure/function/LGE; Oxford mapping; Glasgow extracardiac anatomy). Results were discussed on a weekly basis by a disseminated panel of experts.

Volumes and function
Left ventricular (LV) structure and function was analysed using a clinically validated artificial intelligence (AI) platform. Right ventricles and atria were analysed manually, in detail, trabeculations of the RV were ignored, and a smooth endocardial border was drawn to improve reader reproducibility.
LGE A standard operating procedure was developed for late gadolinium enhancement (LGE), with all analyses performed by three experienced independent observers using Circle CVI42 version 5.13.5 (Circle Cardiovascular Imaging Inc., Calgary, Alberta, Canada). Furthermore, all LGE analysis were reviewed by two level 3 accredited CMR supervisors.
LGE was defined as area of hyperintense signal in the myocardium on the PSIR images. The presence of LGE in most cases was obvious but where there was uncertainty about the presence of LGE, all long axis LGE, contiguous SAX slices, cine images or, where available, dark blood LGE were reviewed to confirm the results.
LGE was qualitatively evaluated as : A)infarct, subendocardial or transmural scar conforming to a coronary territory; B)non-ischaemic, subepicardial or intramyocardial scar-a category that includes most myocarditis related scar; C)Both A and B, dual pathology; D)micro-infarction, bright subsegmental areas of scar sometimes in multiple territories; E)likely pre-existing scar (where there is a known disease causing a certain pattern of LGE e.g. amyloid, sometimes with prior imaging) or nonspecific scar; F)no scar (figure 2 and Figure S1).
Furthermore, in scans considered to have LGE, a quantitative LGE analysis was performed by semi-automated signal intensity analysis. Epicardial then endocardial contours were manually drawn, with care taken to exclude artefacts, blood pool, fat and pericardium. An area of normal remote myocardium (the darkest area of myocardium throughout the whole SAX stack) was defined alongside identification of an area with visually the greatest increased signal intensity.
LGE was then obtained using the 5SD techniques are recorded. The percentage of LGE by these techniques was then multiplied by the absolute LV mass on cine images to determine LGE mass. Quantitative assessment was performed by semi-automated signal intensity analysis using a 5-SD approach [1] 25.
LGE of <1% of the myocardium at the right ventricular (RV) insertion points only was ignored.

Image analysis of T1-and T2-maps
Global T1, T2 and ECV analyses were performed blinded to the clinical information on commercially-available postprocessing software (cmr42, Circle Cardiovascular Imaging, Calgary, Alberta, Canada, v5.10). Endo-and epicardial contours were manually placed within the left ventricular myocardium on short-axis T1, T2-maps, with care to avoid partial volume with surrounding tissue, such as fat or blood pool. Raw images were examined for breathing or cardiac motion, or SSFP artefacts. Where available, quality control maps for 'goodness of fit' were assessed for image quality as previously published. Individual average T1, T2 and ECV results were marked with a quality score depending on the data quality: 0good quality; 1 -minor issues, <50% myocardial segments affected; 2 -major issues, >50% image data corrupted; 3not analysable or missing data. Scores 0-1 were considered reliable and adequate reportable myocardial coverage. Conversely, the estimates with the quality scores 2-3 were recommended for rejection from the final statistical analysis. For ECV quantification, additional regions of interest were also placed in LV blood pool in both the native and post-Gd T1-maps, avoiding artefacts and papillary muscles. ECV was calculated from the native and post-contrast T1 in accordance with the previously published formula: ECV = (1−haematocrit) × (ΔR1myocardium/ΔR1blood), where R1 = 1/T1.
Harmonisation: Mapping image analysis for global T1/T2/ECV values was performed by a single image analyst (EL) with over 5 years' experience in mapping image analysis and over 10 years in CMR data analysis. The observer has undergone the standardised training; complex datasets were referred for internal reviews within the OCMR core lab (SKP, VMF). For the different sites, scanners and/or sequences, local normal ranges for T1-and T2-mapping were obtained directly from the sites according to SCMR guidelines, or ShMOLLI T1-mapping norms were used after the sequence conformance was validated using phantoms, as appropriate. The normal ranges were all expressed as normal mean ± SD for each site. In line with prior observation, the variation in the reported normal SDs between sites was not suitable for the application of z-scores; instead, the normalised nT1 and nT2 were reported, obtained by dividing the individual T1 and T2 measurements by the corresponding normal mean value for the appropriate site/scanner/sequence combination. In line with prior studies, ECV was deemed to have a satisfactory intrinsic compensation for inter-scanner variability, and thus was used directly.
Where T2 mapping was available matching a slice with LGE, a ROI was drawn to sample the T2 values in both the area of LGE and in remote myocardium and the difference calculated as ∆T2 (T2 in the LGE area -T2 in the remote myocardium).

EXTRA-CARDIAC CMR ANALYSIS
The extracardiac CMR analysis were performed by an experienced Consultant Radiologist with 20+ years' experience in cardiovascular & thoracic radiology. Findings were divided into those potentially related to Covid -19 itself (i.e. the manifestations of pneumonitis or heart failure) and those that are truly incidental but potentially important for patient care. In particular, they were divided into the following sections: 1 -Potential Covid-19 Related -1A Pneumonitis Related Changes -graded as 0 -No abnormality 1 -Minor peripheral pulmonary signal changes, predominantly posterior and thought potentially due to either Covid-19 pneumonitis or just dependent change 2 -Peripheral pulmonary signal changes being greater than grade 1 and peripheral, patchy, non-dependent thought likely to be due to Covid-19 pneumonitis in pandemic scenario 3 -Extensive pulmonary signal changes compatible with severe Covid-19 pneumonitis in pandemic scenario.
Modifiers -narrative for findings such as lobar collapse, cavitation etc. which were unusual

-Potentially Clinically Significant Pre-Existing Cardiac Incidental Findings -
Single free text field for a narrative description of anything potentially important spotted e.g. valvular stenosis &/or incompetence, intracardiac thrombus, congenital abnormality, obvious chamber abnormality, features of cardiomyopathy such as focal hypertrophy, sternal wires, valve replacements etc.

-Potentially Clinically Significant Incidental Extracardiac Findings -
Single free text field for a narrative description of anything potentially important spotted, the following were thought the most likely scenarios (although in real terms unlikely) (-Lung or pleural mass -suspicion of cancer; Aortic Aneurysm; Mediastinal mass -e.g. lymphadenopathy; Skeletal abnormality -suspicion of cancer; Upper abdominal organ -suspicion of cancer or potentially important benign condition (e.g. hepatic or renal masses, gallstones and similar); Abnormally raised diaphragm N.B. Small hiatus hernias, small hepatic and renal cysts, colonic diverticulosis and similar common findings of little clinical importance were not recorded (only large hiatus hernias and abnormal/complex looking cysts).
Supplementary results:

Figure S1: Patterns of LGE in Covid+/Troponin+ patients
Patterns of LGE: A) Infarct (bright, subendocardial, territorial); B) Non-ischemic (mid myocardial, less bright, more diffuse ); C) Dual pathology (both A and B); D) Microinfarcts (bright spots of subsegmental LGE, up to 10 grams, often but not exclusively subendocardial and potentially in more than one territory); E1) Chronic, known preexistent disease (in just 4 cases: hypertrophic cardiomyopathy, dilated cardiomyopathy, cardiac amyloidosis, pulmonary hypertension) E3) Non-specific (unequivocal LGE that both cannot be considered normal but insufficient to assign with certainty to any other category). F) No or trivial LGE (minor RV insertion point, trabecular or septal perforator LGE being therefore ignored).

Figure S2: Patterns of LGE in controls
Patterns of LGE in controls (in brackets the features of each): A) Infarct (bright, sub-endocardial, territorial); B) Non-ischaemic (mid myocardial, less bright, more diffuse); C) Dual pathology(both a and b); D) Microinfarcts (bright spots under half a segment, often a few grams of LGE often but not exclusively subendocardial and potentially in more than one territory); E) No LGE or non-significant LGE (minor RV insertion point LGE alone or trabecular LGE alone or septal perforator LGE alone, that can be considered normal).
LGE: Late Gadolinium Enhancement Figure S3: Example late gadolinium enhancement quantification A single case, one of the 519 in this study with corelab LGE quantification. Here with red: endocardium; green: epicardium. The blue contour on slice 7 is defining the standard deviation of remote myocardium permitting the yellow pixels to be defined (signal >5 standard deviations above remote). Figure S4 Normalized T1, Normalized T2 and Global Extracellular volume values in the three populations.